Evaluation of digital imaging stay-green as a method of indirect selection for grain yield in maize

dc.contributor.author Beltran, Juan
dc.contributor.department Agronomy
dc.contributor.majorProfessor Dr. Anthony Assibi Mahama
dc.contributor.majorProfessor Dr. Thomas Lubberstedt
dc.date 2021-01-07T21:37:45.000
dc.date.accessioned 2021-02-25T00:03:19Z
dc.date.available 2021-02-25T00:03:19Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2020
dc.date.embargo 2020-10-06
dc.date.issued 2020-01-01
dc.description.abstract <p>Stay-green has been used in the past as a secondary trait for indirect selection in grain yield for maize. Stay-green is usually successfully used in stressed environments, low nitrogen and drought, but tends to have poor heritability in the absence of stress compared to grain yield, in contrast to grain yield which tends to drop under stressed environments. This leads to stay-green being overshadowed by other popular secondary traits such as anthesis silking interval. Some of the variability in stay-green is produced by subjectivity. With the use of unmanned aerial devices or drones becoming more popular, imaging was taken for a set of ERA Pioneer hybrids grown under well-watered and drought stress treatments to eliminate statistical noise and improve heritability and correlations. Images for these plots produced RGB values which were then converted to a green leaf index to substitute for conventional stay-green.</p> <p>Genetic correlation and heritability values were computed for full water and drought stress conditions, with drought stress as the control. Heritability was high for both grain yield and stay-green. Indirect selection efficiency was found to still be more efficient under a drought stress condition. However, UAD stay-green was able to provide significance values for the full water condition, something rarely found in previous research with conventional stay-green for non-stressed environments.</p>
dc.format.mimetype Word
dc.identifier archive/lib.dr.iastate.edu/creativecomponents/629/
dc.identifier.articleid 1682
dc.identifier.contextkey 19689672
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath creativecomponents/629
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/93749
dc.source.bitstream archive/lib.dr.iastate.edu/creativecomponents/629/Creative_Component_Juan_Beltran__1_.docx|||Sat Jan 15 01:19:32 UTC 2022
dc.source.bitstream archive/lib.dr.iastate.edu/creativecomponents/629/auto_convert.pdf|||Sat Jan 15 01:19:33 UTC 2022
dc.subject.disciplines Plant Breeding and Genetics
dc.subject.keywords maize
dc.subject.keywords indirect selection
dc.subject.keywords stay-green
dc.subject.keywords UAD
dc.title Evaluation of digital imaging stay-green as a method of indirect selection for grain yield in maize
dc.type article
dc.type.genre creativecomponent
dspace.entity.type Publication
relation.isOrgUnitOfPublication fdd5c06c-bdbe-469c-a38e-51e664fece7a
thesis.degree.discipline Plant Breeding
thesis.degree.level creativecomponent
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